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DBMS > Databricks vs. Datastax Enterprise vs. QuestDB vs. RDF4J

System Properties Comparison Databricks vs. Datastax Enterprise vs. QuestDB vs. RDF4J

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonDatastax Enterprise  Xexclude from comparisonQuestDB  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
DescriptionThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.DataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform.A high performance open source SQL database for time series dataRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelDocument store
Relational DBMS
Wide column storeTime Series DBMSRDF store
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score76.33
Rank#17  Overall
#3  Document stores
#11  Relational DBMS
Score6.31
Rank#57  Overall
#4  Wide column stores
Score2.48
Rank#115  Overall
#9  Time Series DBMS
Score0.71
Rank#231  Overall
#9  RDF stores
Websitewww.databricks.comwww.datastax.com/­products/­datastax-enterprisequestdb.iordf4j.org
Technical documentationdocs.databricks.comdocs.datastax.comquestdb.io/­docsrdf4j.org/­documentation
DeveloperDatabricksDataStaxQuestDB Technology IncSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release2013201120142004
Current release6.8, April 2020
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava (Zero-GC), C++, RustJava
Server operating systemshostedLinux
OS X
Linux
macOS
Windows
Linux
OS X
Unix
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyes infoschema-free via InfluxDB Line Protocolyes infoRDF Schemas
Typing infopredefined data types such as float or dateyesyesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.yesnono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLwith Databricks SQLSQL-like DML and DDL statements (CQL); Spark SQLSQL with time-series extensionsno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Proprietary protocol infoCQL (Cassandra Query Language)
TinkerPop Gremlin infowith DSE Graph
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languagesPython
R
Scala
C
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
Java
PHP
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesnonoyes
Triggersyesnoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infono "single point of failure"horizontal partitioning (by timestamps)none
Replication methods infoMethods for redundantly storing data on multiple nodesyesconfigurable replication factor, datacenter aware, advanced replication for edge computingSource-replica replication with eventual consistencynone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Tunable Consistency infoconsistency level can be individually decided with each write operation
Immediate Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDno infoAtomicity and isolation are supported for single operationsACID for single-table writesACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoin-memory storage is supported as well
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infothrough memory mapped files
User concepts infoAccess controlAccess rights for users can be defined per objectno
More information provided by the system vendor
DatabricksDatastax EnterpriseQuestDBRDF4J infoformerly known as Sesame
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
» more
DataStax Enterprise is scale-out data infrastructure for enterprises that need to...
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Relational model with native time series support Column-based storage and time partitioned...
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Competitive advantagesSupporting the following application requirements: Zero downtime - Built on Apache...
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High ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more
Typical application scenariosApplications that must be massively and linearly scalable with 100% uptime and able...
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Financial tick data Industrial IoT Application Metrics Monitoring
» more
Key customersCapital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and...
» more
Banks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
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Market metricsAmong the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...
» more
Licensing and pricing modelsAnnual subscription
» more
Open source Apache 2.0 QuestDB Enterprise QuestDB Cloud
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